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Practical Deep Learning with PyTorch


Software Requirements :
CPU Software Requirements
CPU Installation of PyTorch
PyTorch with GPU on AWS
PyTorch with GPU on Linux
PyTorch with GPU on MacOSX

PyTorch Fundamentals: Matrices :
Matrix Basics
Seed for Reproducibility
Torch to NumPy Bridge
NumPy to Torch Bridge
GPU and CPU Toggling
Basic Mathematical Tensor Operations
Summary of Matrices

PyTorch Fundamentals: Variables and Gradients :
Variables
Gradients
Summary of Variables and Gradients

Linear Regression with PyTorch :
Linear Regression Introduction
Linear Regression in PyTorch
Linear Regression From CPU to GPU in PyTorch
Summary of Linear Regression

Logistic Regression with PyTorch :
Logistic Regression Introduction
Linear Regression Problems
Logistic Regression In-depth
Logistic Regression with PyTorch
Logistic Regression From CPU to GPU in PyTorch
Summary of Logistic Regression

Feedforward Neural Network with PyTorch :
Logistic Regression Transition to Feedforward Neural Network
Non-linearity
Feedforward Neural Network in PyTorch
More Feedforward Neural Network Models in PyTorch
Feedforward Neural Network From CPU to GPU in PyTorch
Summary of Feedforward Neural Network

Convolutional Neural Network (CNN) with PyTorch :
Feedforward Neural Network Transition to CNN
One Convolutional Layer, Input Depth of 1
One Convolutional Layer, Input Depth of 3
One Convolutional Layer Summary
Multiple Convolutional Layers Overview
Pooling Layers
Padding for Convolutional Layers
Output Size Calculation
CNN in PyTorch
More CNN Models in PyTorch
CNN Models Summary
Expanding Model's Capacity
CNN From CPU to GPU in PyTorch
Summary of CNN

Recurrent Neural Networks (RNN) :
Introduction to RNN
RNN in PyTorch
More RNN Models in PyTorch
RNN From CPU to GPU in PyTorch
Summary of RNN

Long Short-Term Memory Networks (LSTM) :
Introduction to LSTMs
LSTM Equations
LSTM in PyTorch
More LSTM Models in PyTorch
LSTM From CPU to GPU in PyTorch
Summary of LSTM

What's Next? :
What's Next?